Statistical Geometry Processing

Requirements / organisational issues

1. Programming (there will be practical assignments)
   
2. Mathematics (there will be quite some math)
   
3. Basic knowledge in Computer Graphics and Statistical Learning
   
(for example from Modelling lecture(s), Computer Vision, CG & ML lectures)

Digital teaching

Contents

1. Recap graphics & statistical learning (short, if requested)
   
2. Supplementary statistical models/concepts
   
[list]

3. "Graphical Models" (in a statistical sense)
   
4. Markov Random Fields
   

1. Differential geometry
   
2. Parametrization
   
3. Fourier analysis on Manifolds
   

1. 3D scanners
   
2. Reconstruction from images
   

1. Shape spaces (variational, probabilistic, intrinsic)
   
2. Shape matching
   
3. Symmetry detection
   
4. Generative statistical models
   

Dates